Public health interventions and epidemic intensity during the 1918 influenza pandemic

By R. Hatchett, C. Mecher, Marc Lipsitch. Proceedings of the National Academy of Sciences of the United States of America, 2007

694 citations recorded by the source corpus.

Nonpharmaceutical interventions (NPIs) intended to reduce infectious contacts between persons form an integral part of plans to mitigate the impact of the next influenza pandemic. Although the potential benefits of NPIs are supported by mathematical models, the historical evidence for the impact of such interventions in past pandemics has not been systematically examined. We obtained data on the timing of 19 classes of NPI in 17 U.S. cities during the 1918 pandemic and tested the hypothesis that early implementation of multiple interventions was associated with reduced disease transmission. Consistent with this hypothesis, cities in which multiple interventions were implemented at an early phase of the epidemic had peak death rates ≈50% lower than those that did not and had less-steep epidemic curves. Cities in which multiple interventions were implemented at an early phase of the epidemic also showed a trend toward lower cumulative excess mortality, but the difference was smaller (≈20%) and less statistically significant than that for peak death rates. This finding was not unexpected, given that few cities maintained NPIs longer than 6 weeks in 1918. Early implementation of certain interventions, including closure of schools, churches, and theaters, was associated with lower peak death rates, but no single intervention showed an association with improved aggregate outcomes for the 1918 phase of the pandemic. These findings support the hypothesis that rapid implementation of multiple NPIs can significantly reduce influenza transmission, but that viral spread will be renewed upon relaxation of such measures.

Subfields: Economics and Econometrics, Epidemiology, Modeling and Simulation

View Paper: https://www.semanticscholar.org/paper/cf6f37e906cc0c435f1f149b249a9e421514ac51

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Citations in the corpus

COVID-19 control in China during mass population movements at New Year (2020, neutral): “[11] [12] [13] [14] [15] [16] [17] A single social distancing policy can cut epidemic spread, but usually multiple such policies-including more restrictive mea sures such as isolation and quarantine-are implemented in combination to boost effectiveness.”
Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases (2008, background): “Both can be achieved by nonpharmaceutical interventions such as school closure, travel restrictions, and contact tracing, or by health-care interventions such as vaccination and use of antiviral or antibiotic agents [2, [10] [11] [12] [13] .”
The spread of awareness and its impact on epidemic outbreaks (2009, background): “Efforts to assess the potential for prevention of future outbreaks of contagious diseases have motivated previous studies on the effects of social distancing (11, 12) which, however, focused on behavioral changes imposed by a central organization on the population level.”
Cross-Species Virus Transmission and the Emergence of New Epidemic Diseases (2008, background): “taken in 1918 were effective in controlling the influenza pandemic of that year (8, 38).”
Partisanship, health behavior, and policy attitudes in the early stages of the COVID-19 pandemic (2020, background): “Because an effective public health response to a rapidly-moving influenza pandemic such as COVID-19 requires consistent participation and collective action across communities [47,48] in addition to broader public health interventions [49], our findings have disturbing implications for health crisis ”
FluTE, a Publicly Available Stochastic Influenza Epidemic Simulation Model (2010, background): “Mathematical and computer models of epidemics have contributed to our understanding of the spread of infectious disease and the measures needed to contain or mitigate them [1–9].”
Coupled disease–behavior dynamics on complex networks: A review (2015, background): “Incorporating adaptive behavior into a model of disease spread can provide important insight into population health outcomes, as the activation of social distancing and other nonpharmaceutical interventions (NPIs) have been observed to have the ability to alter the course of an epidemic [50] [51] [5”
COVID-19: Prevention and control measures in community (2020, background): “In the influenza pandemic in 1918, the importance of quarantine measures was demonstrated very clearly [13].”